#370 - AMA #76： Peter evaluates longevity drugs, aspirin for CVD, and strategies to improve muscle mass — proven, promising, fuzzy, noise, or nonsense？
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Summary
In this episode, we revisit the proven, promising, fuzzy, noise, nonsense scale and apply it to a variety of commonly inquired about and hot button topics. We start with a quick reset on what each bucket means and define them, of course, and then we walk through every topic where we land on.
Transcript
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Hey everyone, welcome to a sneak peek, ask me anything or AMA episode of the drive podcast.
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I'm your host, Peter Atiyah. At the end of this short episode, I'll explain how you can access
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the AMA episodes in full, along with a ton of other membership benefits we've created,
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or you can learn more now by going to peteratiyahmd.com forward slash subscribe.
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So without further delay, here's today's sneak peek of the ask me anything episode.
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Welcome to ask me anything AMA episode number 76. In today's AMA, we revisit the proving,
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promising, fuzzy, noise, nonsense scale and apply it to a variety of commonly inquired about and
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hot button topics. We start with a quick reset on what each bucket means and define them, of course,
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and then we walk through every topic where we're going to land on. So the goal of this episode is
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that if you're coming to this topic without any previous background, or you just want the TLDR,
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this is the place for you. We group the topics by the intended outcome. There are three categories
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today. Drugs for gyroprotection, where we cover GLP-1 agonists, SGLT-2 inhibitors, methylene blue,
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and telomere lengthening supplements. Talk about low dose aspirin for CVD prevention. And then we
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look at interventions to improve muscle mass, talking specifically about protein, but also
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folistatin gene therapy. If you're a subscriber and want to watch the full video of this podcast,
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you can find it on the show notes page. And if you're not a subscriber, you can watch the sneak
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peek of this video on our YouTube page. So without further delay, I hope you enjoy AMA 76.
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All right. Peter, Artia, doctor, podcaster, author, speaker, bad chess player. How are you doing
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today? Hey, hey, hey, hey, hey, hey, hey. You could say shepherd in there. You don't have to,
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you don't have to take sheep shots. Shepherd of diabetic sheep, race car driver. Anything else
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missing? Oh, that's good. That's good. All right. I just didn't want to forget the diabetic sheep
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out there. That's true. That's true. How's the day going today? Started out good. Then took a little
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dip with the follow-up chess match, but there's a recurring theme here that you, I know you just
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love picking this scab. Well, I just, sometimes you think about feats like Tom Brady, right? Like
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what he went through. Greatest of all time, right? Yeah. People who come back from injuries.
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Tamar Hamlin, like almost died, came back and played. I mean, like you getting second in a four
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person in-house chess tournament with two children has to be up there, right? Listen,
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we all started playing at the same time. Pogacar just won the tour again, went through two in a row,
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grueling, not as mentally tough as what you went through though, a month ago.
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I would argue what I go through on the daily, trying to just make sure I don't get beat by an eight-year-old
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in chess is at least on par mentally with some of the feats you're talking about.
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We need to have Tom on the podcast and you should ask him about it. Which one was harder? All those
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Super Bowls. Is it harder to be down 28 to three, having thrown a pick six in the Super Bowl or
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succumbing to an eight-year-old's gambit, which is tougher? To be fair, there is a real chance the
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eight-year-old might've talked more trash than what was going on in the Super Bowl, which says
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something. Yep. All right. So today's AMA, not about chess, going to be a little different.
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So what we're going to do is cover a variety of topics, looking at it through a certain lens,
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which is we are going to take concepts and things that we've talked about before, some new things
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that we haven't talked about before, that we get asked about a lot. And instead of going super deep
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in them, we're going to kind of summarize them into how you think about them. And we're going to do it
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into five different buckets. And those buckets are proven, promising, fuzzy, noise, nonsense.
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People who have listened for a bit will remember this. We did this in episode 300 of the podcast,
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which was back in May, 2024. So it's been a little bit, but people really liked it because it allowed us to
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cover a variety of topics. It allowed us to summarize them and it allowed us to kind of look
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at them in apples to apples comparison with what we know about them and how people should be thinking
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about it. So in today's episode, we are going to look at some geroprotective drugs like GLP-1s,
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things like Ozempic, SGLT2 inhibitors, both of which we talked about before. We're going to look at
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methylene blue and telomere lengthening supplements. Those are kind of newer. We're going to look at what we
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know about low-dose aspirin and cardiovascular disease prevention. And then we're going to look
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at interventions that can help improve muscle mass, things like protein, folistatin gene therapy,
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et cetera. Hopefully a good variety of things for people. Hopefully kind of a way to go through it
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where people can kind of look, get clear, clean takeaways. With that said, anything you want to add
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before we get rolling? No, but maybe I will just remind people or for folks who are new to the
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program, what these categories mean. So you mentioned five and we're starting from the most
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promising or the closest to quote unquote truth, which we're calling proven. Although I put proven
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in quotes because technically nothing in biology is proven, right? It's not like mathematics where you
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prove something and write QED at the end and never have to think about it again. So proven would be
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as close to well-established claim as you're going to find. The implication for us, of course, is you've
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got lots of high quality, consistent data. The category beneath that would be promising. This is a
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category where the claims look good. There are data to support it, but maybe we're still waiting on
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replication or maybe most of the data are moving in one direction, but not all of it or something like
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that. Category beneath that we call fuzzy. And this means there are some data around the claim,
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but they are really inconsistent and incomplete. So overall, you would say the data quality here is
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not that great, but there's probably a signal. Beneath that, we have noise. So here we have
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something where there are just frankly no real meaningful results. So noise is something that,
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it's not that I'm saying you shouldn't pay attention to it, but you clearly don't want to be
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distracted by it. And it's best to wait and see if noise declares itself by going up to fuzzy with the
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presence of some data as it works its way up the chain or whether data actually emerge that put it
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in the final category, which is actual nonsense. So again, nonsense means we actually have data and the
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data refute the claim being made. So as far as we can tell, this is as close to disproven as you'll
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be. So again, those are the five categories. Just kind of keep that in mind as we apply our judgments
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to these things and keep in mind as well that these are fluid. Things can move up and down these chains
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in the presence of new information. Yeah. And I think I always like to anchor people to this. And so
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we've talked about it before, but I do think it's helpful, which is sometimes I think in today's day and age
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where people are very confident in their opinions and usually kind of stick to them. You see it a lot
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in nutrition where it's like, you just get in a camp and you stay with it. Do you just want to talk a
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little bit about your idea of strong convictions, loosely held and why you think it might be
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counterintuitive when people change mind and something goes from proven to promising or it goes
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up and down, but just how you think about when new data comes, you just have to be
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unemotional to it and just take signs for science. Yeah. Look, I think first and foremost,
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that's an attribute of great scientists. So if you look at what separates good scientists from
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great scientists, that would probably be one of the characteristics. A great scientist is not married
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to being right. They're married to knowing what is right and they're going to go wherever the data
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take them. But honestly, the first time I heard that expression to have strong convictions loosely
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held was actually from a friend of mine who at the time was running a hedge fund. He's since retired,
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but he said, look, that's the key to being a good investor is you have to have strong convictions
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because you're going to be putting a lot of capital at risk, but those convictions have to be
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loosely held. So the moment that data emerge, the change your thesis for investment, you have to be
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flexible enough to move as opposed to double down. And the reason I think that this is such an
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important part of investing is in science, if you're wrong, the price is not that severe.
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In fact, without calling out or embarrassing anybody, there are lots of people who have taken
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positions on things that are just so patently incorrect 20 and 25 years later, and yet they just
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can't let go of their baby. They can't kill their baby. And so frankly, they just make fools out of
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themselves continuing to cling to ridiculous beliefs, but there's actually no real price they're
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paying for that other than within the scientific community they're laughed at. But you can't be an
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investor. You can't be a money manager with that type of mentality because you'll be out of business.
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And so in the final analysis, the dollars talk louder than anything else. And if you continue to
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double down on horrible positions, you will lose the money of your LPs and ultimately you will be broke.
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So I think that's sort of why it's a great idea to be thinking about through the lens of how an
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investor functions. And so I think we just have to all try to do that. It's hard. It's hard to kill
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your babies, but that was the expression. Those were the exact words that were used when I first showed
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up in the lab and first started doing experiments and first started getting my data and trying to put
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hypotheses together and make sense of what I was seeing. You can have the most beautiful,
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beautiful hypothesis ever. And it can be categorically slayed by ugly facts. And that's
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paraphrasing a quote. God, I don't remember who actually said that quote, but it's a sort of famous
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quote in science. Yeah. I think it's just good for people to kind of anchor that too. So starting off,
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if you had to put the following statement into one of those categories, where would it be? Which is
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the next in-house tournament, Peter Atiyah takes first place?
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Listen, I believe I have the potential to beat my young boys in chess, provided I don't get
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distracted by the smack talk. In my defense today, by the way, I know you don't play chess, but just so
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you understand, I promoted a pawn to a second queen on the 25th move. Do you understand what an
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advantage I had in this game today? I've got two queens on the board and I was ahead on material
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before that promotion. This was a bloodbath. And then he starts yapping so much and makes what
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looks like an idiotic blunder, exposing his rook to my newest queen. So of course I take the free rook,
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but I was so dumb when I did it that I didn't notice that he moved his bishop out of the way
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what looked like a blunder. So he sacrificed his rook to put his bishop in a way to basically
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create what's called a battery against my king. And the next move, he checkmated me.
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So you could say, okay, I got beat. Yes, I did. But part of it is I was distracted by how much he
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was yapping. So all I really need to do to up my game is just not get distracted. I think I have a
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good chance to win the next in-house tournament. I do love your kryptonite is second graders who
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talk trash, whether it's chess, whether it was the kid who was just giving you tons of crap for
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drinking a diet soda at the school lunch, wherever it is. There could literally be a sitcom of me
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going through my life, just getting broken down by eight-year-olds, just getting put in my place.
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It's like the Seinfeld episode where the shrimp comment, a day later, he rethinks of what the
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comeback should have been. I just anticipate that's you like going to sleep at night being like,
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oh man, when Aries said this, if I would have responded with this, I would have got him so bad.
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Next time, next time, I'm not going to let that eight-year-old talk that trash to me.
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Well, real thing we're going to start with, geoprotective drugs. So there's a lot of
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questions about drugs that have metabolic health effects and what that means for anti-aging.
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So instead of just looking at this improves metabolic health, is there something special
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about those that can also be anti-aging? And on a side note, just it'll be good to explain what
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geoprotective drugs are. We've done it before, but I think it's good for a quick reminder. But
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outside of that, the biggest drug that is in the news all day, every day, GLP-1s,
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Ozempic, Trisepatide, Wigovi, you name it, everyone's heard of it. We've done a lot about
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that. So the question is, do we know anything if they have a unique anti-aging effect that actually
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improves lifespan outside of the metabolic health effects they have?
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